HEC Montréal, Canada, 6 - 8 mai 2013

Journées de l'optimisation 2013

HEC Montréal, Canada, 6 — 8 mai 2013

Horaire Auteurs Mon horaire

WC3 Méthodes d'optimisation en ingénierie d'aérostructures / Optimization methods in aerostructural engineering

8 mai 2013 15h30 – 17h10

Salle: Gérard Parizeau

Présidée par Sylvain Arreckx

3 présentations

  • 15h30 - 15h55

    Static Aeroelastic Design Optimization of Lightweight Structures: Computational Challenges and Opportunities

    • Graeme Kennedy, prés., University of Toronto

    Static aeroelastic design optimization of flexible, lightweight aircraft involves the simultaneous design of both aerodynamics and structures. Static aeroelastic analysis itself is a computationally expensive problem that often requires the use of high-performance computing techniques. Simulation-based design optimization of static aeroelastic systems presents many computational challenges and opportunities for the application of novel optimization techniques that have the potential to reduce computational times.

  • 15h55 - 16h20

    Quasi-Newton Jacobian Estimates for Matrix-Free Structural Optimization

    • Andrew Lambe, prés., University of Toronto
    • Joaquim Martins, University of Michigan

    In structural optimization problems with failure constraints, the computational cost is dominated by computing the gradients of all the constraints. Using a "matrix-free" optimizer can reduce this cost significantly by requiring only appropriate matrix-vector products with the full constraint Jacobian. To keep the total number of matrix-vector products small, we will advocate estimating the constraint Jacobian within the matrix-free optimizer using a quasi-Newton method. Results from structural test problems demonstrate that the computational cost scales well compared to traditional SQP algorithms.

  • 16h20 - 16h45

    Implementation of a Matrix-Free Augmented Lagrangian Algorithm

    • Sylvain Arreckx, prés., Polytechnique Montréal
    • Dominique Orban, GERAD - Polytechnique Montréal

    In many applications, problems are so large that we cannot compute/store explicit Jacobians and don't have access to Hessian information. We will outline a matrix-free algorithm for solving nonlinear problems with both
    equalities and inequalities. Our algorithm is based on an augmented Lagrangian approach and relies on matrix-vector products only. We also show some numerical results on the CUTEr and COPS collections.